Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use mcamara/whisper-tiny-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcamara/whisper-tiny-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mcamara/whisper-tiny-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mcamara/whisper-tiny-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("mcamara/whisper-tiny-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mcamara/whisper-tiny-dv: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/mcamara/whisper-tiny-dv/resolve/main/training_args.bin
- Command line
-
hf download hf://mcamara/whisper-tiny-dv/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mcamara/whisper-tiny-dv/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- f5a9d0b18584cc3f53a270c905eca2e47828556a13c577decd0a6abce9ada75e
- Size of remote file:
- 4.16 kB
- SHA256:
- dd294176b1d474a85b7fdb185ffb6207b41ae7176e504b290f9c9bc6d8ea08f7
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